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Davis, Glenn M.; Hanzsek-Brill, Melissa B.; Petzold, Mark Carl; Robinson, David H. – Journal of the Scholarship of Teaching and Learning, 2019
Educational institutions increasingly recognize the role that student belonging plays in retention. Many studies in this area focus on helping students improve a sense of belonging before they matriculate or identifying belonging as a reason for their departure. This study measures students' sense of belonging at key transition points during the…
Descriptors: School Holding Power, Predictive Measurement, Instructional Effectiveness, Academic Persistence
Rajabalee, Yousra Banoor; Santally, Mohammad Issack; Rennie, Frank – International Journal of Distance Education Technologies, 2020
This paper reports the findings of a research using marks of students in learning activities of an online module to build a predictive model of performance for the final assessment of the module. The objectives were (1) to compare the performances of students of two cohorts in terms of continuous learning assessment marks and final learning…
Descriptors: Performance Factors, Electronic Learning, Learning Analytics, Learning Activities
Huang, Liuli; Roche, Lahna R.; Kennedy, Eugene; Brocato, Melissa B. – International Journal of Higher Education, 2017
Many researchers have explored the relationships between the likelihood of graduating from college and demographic and pre-college factors such as gender, race/ethnicity, high school grade point average (GPA), and standardized test scores. However, additional factors such as a student's college major, home address, or use of learning support in…
Descriptors: Graduation Rate, Predictor Variables, Predictive Measurement, Predictive Validity
Mertes, Scott J.; Hoover, Richard E. – Community College Journal of Research and Practice, 2014
Retention is a complex issue of great importance to community colleges. Several retention models have been developed to help explain this phenomenon. However, these models typically have used four-year college and university environments to build their foundations. Several researchers have attempted to identify predictor variables using…
Descriptors: Community Colleges, Predictor Variables, College Freshmen, Academic Persistence
Comer, Keith; Broght, Erik; Sampson, Kaylene – Journal of Institutional Research, 2011
Building on Shulruf, Hattie and Tumen (2008), this work examines the capacity of various National Certificate in Educational Achievement (NCEA)-derived models to predict first-year performance in Biological Sciences at a New Zealand university. We compared three models: (1) the "best-80" indicator as used by several New Zealand…
Descriptors: Science Achievement, Biology, Secondary School Science, National Competency Tests
Smith, Vernon C.; Lange, Adam; Huston, Daniel R. – Journal of Asynchronous Learning Networks, 2012
Community colleges continue to experience growth in online courses. This growth reflects the need to increase the numbers of students who complete certificates or degrees. Retaining online students, not to mention assuring their success, is a challenge that must be addressed through practical institutional responses. By leveraging existing student…
Descriptors: Academic Achievement, At Risk Students, Prediction, Community Colleges
Downes, Beverley – Australian University, 1976
A Model predicts a student's academic performance in his first year in a particular department at a university. It uses an aggregate selection score based on aggregate results obtained at a public examination along with a measure of the student's ability in one or more specific subjects or areas relevant to the department. (LBH)
Descriptors: Academic Achievement, Admission (School), College Freshmen, Foreign Countries
Peer reviewedOtt, Mary Diederich – Research in Higher Education, 1988
Logistic regression was employed to analyze predictors of academic performance (academic dismissal versus satisfactory performance) for first-time freshmen after one semester in an eastern state university. The analyses indicated that academic performance was highly related to high school academic grade point average. (Author/MLW)
Descriptors: Academic Achievement, Academic Failure, College Freshmen, Expulsion
Peer reviewedChatman, Steven P. – Research in Higher Education, 1986
The difference between accepted and enrolling students was modeled over a 30-week period using total number of students accepted, mean composite SAT scores, and mean high school quarter rank. The enrollment yield and academic ability difference functions were collectively modeled for the university and separately for each academic college.…
Descriptors: Academic Ability, Academic Achievement, College Applicants, College Freshmen
Fox, Richard N. – 1984
The first phase of a study to predict retention and withdrawal among disadvantaged students at an urban commuter institution is described. Variable selection for the study was guided by Tinto's (1975) and Bean's (1982) models. Pilot testing was undertaken to estimate some psychometric characteristics of Pascarella and Terenzini's institutional…
Descriptors: Academic Persistence, College Freshmen, Commuting Students, Disadvantaged
Bean, John P. – 1981
A theoretical model of turnover in work organizations was applied to the college student dropout process at a major midwestern land grant university. The 854 freshmen women subjects completed a questionnaire that included measures for 14 independent variables: grades, practical value, development, routinization, instrumental communication,…
Descriptors: College Freshmen, Dropout Attitudes, Dropout Research, Employment Patterns
Sadler, William E.; Cohen, Frederic L.; Kockesen, Levent – 1997
This paper describes a methodology used in an on-going retention study at New York University (NYU) to identify a series of easily measured factors affecting student departure decisions. Three logistic regression models for predicting student retention were developed, each containing data available at three distinct times during the first…
Descriptors: Academic Persistence, College Freshmen, Dropouts, High Risk Students
Eddins, Diane Dixon – 1982
A model of attrition for specially admitted black students (low high school achievement and low assessed college aptitude) at the University of Pittsburgh was tested. The majority fell into the lower end of a socioeconomic range and often had inadequate precollege preparation. The attrition model was examined using a linear structural equation…
Descriptors: Academic Ability, Academic Achievement, Aptitude Tests, Black Students

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